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add new inference X

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This commit is contained in:
Zhenwen Dai 2014-11-03 13:38:28 +00:00
parent 78be1464be
commit 78b50db138
3 changed files with 149 additions and 0 deletions
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6
GPy/core/parameterization/variational.py
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@ -94,6 +94,9 @@ class VariationalPosterior(Parameterized):
if self.has_uncertain_inputs():
assert self.variance.shape == self.mean.shape, "need one variance per sample and dimenion"
def set_gradients(self, grad):
self.mean.gradient, self.variance.gradient = grad
def _raveled_index(self):
index = np.empty(dtype=int, shape=0)
size = 0
@ -158,6 +161,9 @@ class SpikeAndSlabPosterior(VariationalPosterior):
self.gamma = Param("binary_prob",binary_prob, Logistic(1e-10,1.-1e-10))
self.link_parameter(self.gamma)
def set_gradients(self, grad):
self.mean.gradient, self.variance.gradient, self.gamma.gradient = grad
def __getitem__(self, s):
if isinstance(s, (int, slice, tuple, list, np.ndarray)):
import copy